Currently, and based on the development of relevant biologic therapies, T2-high is the most well-defined endotype of asthma. Although much progress has been made in elucidating T2-high inflammation ...pathways, no specific clinically applicable biomarkers for T2-low asthma have been identified. The therapeutic approach of T2-low asthma is a problem urgently needing resolution, firstly because these patients have poor response to steroids, and secondly because they are not candidates for the newer targeted biologic agents. Thus, there is an unmet need for the identification of biomarkers that can help the diagnosis and endotyping of T2-low asthma.
Ongoing investigation is focusing on neutrophilic airway inflammation mediators as therapeutic targets, including interleukin (IL)-8, IL-17, IL-1, IL-6, IL-23 and tumour necrosis factor-α; molecules that target restoration of corticosteroid sensitivity, mainly mitogen-activated protein kinase inhibitors, tyrosine kinase inhibitors and phosphatidylinositol 3-kinase inhibitors; phosphodiesterase (PDE)3 inhibitors that act as bronchodilators and PDE4 inhibitors that have an anti-inflammatory effect; and airway smooth muscle mass attenuation therapies, mainly for patients with paucigranulocytic inflammation.
This article aims to review the evidence for noneosinophilic inflammation being a target for therapy in asthma; discuss current and potential future therapeutic approaches, such as novel molecules and biologic agents; and assess clinical trials of licensed drugs in the treatment of T2-low asthma.
A 68-year-old male presented to the emergency department with a 24-h history of haemoptysis and fever. The patient also reported a productive cough for 5 years. He was a current smoker (smoking ...history of 80 pack-years) with an otherwise unremarkable past medical history. On examination, his respiratory rate was 24 breaths per min, heart rate was 120 beats per min, temperature 39.2°C and his oxyhaemoglobin saturation was 98% in room air. On auscultation, breath sounds were reduced and end-expiratory crackles were heard over the left lung. Physical examination was otherwise normal. Blood tests showed: white blood cells 14 500 cells·μL
−1
(neutrophils 12 000 cells·μL
−1
, lymphocytes 1900 cells·μL
−1
), haemoglobin 13.9 g·dL
−1
, platelets 256 000 μL
−1
, C-reactive protein (CRP) 128 mg·L
−1
, erythrocyte sedimentation rate 90 mm·h
−1
, normal electrolytes, urea 45 mg·dL
−1
and creatinine 1.22 mg·dL
−1
.
Can you diagnose this 68-year-old male with 24-h history of haemoptysis, 5-year history of productive cough and ipsilateral lung infiltrates?
https://bit.ly/3tyhANB
Corticosteroids in COVID-19: one size does not fit all Gogali, Athena; Kyriakopoulos, Chris; Kostikas, Konstantinos
European respiratory journal/The European respiratory journal,
04/2021, Volume:
57, Issue:
4
Journal Article
A case of a previously healthy man with community-acquired pneumonia who progressed to acute respiratory distress syndrome, with reverse halo sign (RHS) on chest computed tomography, is reported. A ...urinary
Legionella
antigen test was positive for
Legionella pneumophila
. The typical radiographic features of
Legionella
pneumonia are bilateral or unilateral, single or multifocal airspace opacifications (most common), and/or ground-glass opacities. However, a wide variety of radiographic findings have been observed. The RHS is characterized by a central ground-glass opacity surrounded by a more or less complete ring of consolidation. First reported in cryptogenic organizing pneumonia, it was initially thought to be specific for this disease, but was subsequently described in a variety of neoplastic and non-neoplastic pulmonary diseases. In this manuscript, we present a case of
Legionella
pneumonia with a RHS.
The coronavirus disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound wounds in the global healthcare system ...due to its increased transmissibility. Currently, there is an urgent unmet need to identify the underlying dynamic associations among COVID-19 patients and distinguish patient subgroups with common clinical profiles towards the development of robust classifiers for ICU admission and mortality. To address this need, we propose a four step pipeline which: (i) enhances the quality of multiple timeseries clinical data through an automated data curation workflow, (ii) deploys Dynamic Bayesian Networks (DBNs) for the detection of features with increased connectivity based on dynamic association analysis across multiple points, (iii) utilizes Self Organizing Maps (SOMs) and trajectory analysis for the early identification of COVID-19 patients with common clinical profiles, and (iv) trains robust multiple additive regression trees (MART) for ICU admission and mortality classification based on the extracted homogeneous clusters, to identify risk factors and biomarkers for disease progression. The contribution of the extracted clusters and the dynamically associated clinical data improved the classification performance for ICU admission to sensitivity 0.83 and specificity 0.83, and for mortality to sensitivity 0.74 and specificity 0.76. Additional information was included to enhance the performance of the classifiers yielding an increase by 4% in sensitivity and specificity for mortality. According to the risk factor analysis, the number of lymphocytes, SatO2, PO2/FiO2, and O2 supply type were highlighted as risk factors for ICU admission and the percentage of neutrophils and lymphocytes, PO2/FiO2, LDH, and ALP for mortality, among others. To our knowledge, this is the first study that combines dynamic modeling with clustering analysis to identify homogeneous groups of COVID-19 patients towards the development of robust classifiers for ICU admission and mortality.
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•DBNs revealed dynamic associations among major risk factors for ICU admission and mortality.•SOMs yielded homogeneous clusters of patients with dynamically associated profiles.•LGMM identified underlying clusters of individual trajectories with significant differences.•The aggregation of the DBNs and SOMs yielded robust classifiers for ICU admission and mortality.•The inclusion of demographic and treatment-oriented data enhanced the classifiers for mortality.
Although several studies have utilized AI (artificial intelligence)-based solutions to enhance the decision making for mechanical ventilation, as well as, for mortality in COVID-19, the extraction of ...explainable predictors regarding heparin's effect in intensive care and mortality has been left unresolved. In the present study, we developed an explainable AI (XAI) workflow to shed light into predictors for admission in the intensive care unit (ICU), as well as, for mortality across those hospitalized COVID-19 patients who received heparin. AI empowered classifiers, such as, the hybrid Extreme gradient boosting (HXGBoost) with customized loss functions were trained on time-series curated clinical data to develop robust AI models. Shapley additive explanation analysis (SHAP) was conducted to determine the positive or negative impact of the predictors in the model's output. The HXGBoost predicted the risk for intensive care and mortality with 0.84 and 0.85 accuracy, respectively. SHAP analysis indicated that the low percentage of lymphocytes at day 7 along with increased FiO 2 at days 1 and 5, low SatO 2 at days 3 and 7 increase the probability for mortality and highlight the positive effect of heparin administration at the early days of hospitalization for reducing mortality.
Since the World Health Organization (WHO) has declared Artificial Intelligence (AI) as a powerful tool in the fight against COVID-19, multiple studies have been launched aiming to shed light into ...risk factors for ICU admission and mortality. None of the existing studies, however, have captured the dynamic trajectories of hospitalized COVID-19 patients who receive steroids nor have explored trajectory-based mortality indicators. In this work, we present a novel, hybrid approach to address this need. Latent Growth Mixture Modelling (LGMM) was used to analyze the trajectories of patients who received steroids. The patients were then grouped into clusters based on the similarity of their dynamic trajectories. State-of-the art machine learning classifiers are trained on the original dataset with and without dynamic trajectories to assess whether their inclusion can enhance the prediction of mortality. Our results highlight the importance of trajectories for predicting mortality in patients who receive steroids yielding 4% and 5% increase in the sensitivity (0.84) and specificity (0.85). The FiO2 and percentage of neutrophils at day 5, along with the percentage of lymphocytes at day 7, were identified as the main causes for mortality in patients who receive steroids, where the SatO2 levels showed significant alterations in the dynamic trajectories.
Left ventricular assist devices (LVADs) are an established treatment modality for advanced heart failure (HF). It has been shown that through volume and pressure unloading they can lead to ...significant functional and structural cardiac improvement, allowing LVAD support withdrawal in a subset of patients. In the first part of this review, we discuss the historical background, current evidence on the incidence and assessment of LVAD-mediated cardiac recovery, and out-comes including quality of life after LVAD support withdrawal. In the second part, we discuss current and future opportunities to promote LVAD-mediated reverse remodeling and improve our pathophysiological understanding of HF and recovery for the benefit of the greater HF population.
Extrinsic control of cardiomyocyte metabolism is poorly understood in heart failure (HF). FGF21 (Fibroblast growth factor 21), a hormonal regulator of metabolism produced mainly in the liver and ...adipose tissue, is a prime candidate for such signaling.
To investigate this further, we examined blood and tissue obtained from human subjects with end-stage HF with reduced ejection fraction at the time of left ventricular assist device implantation and correlated serum FGF21 levels with cardiac gene expression, immunohistochemistry, and clinical parameters.
Circulating FGF21 levels were substantially elevated in HF with reduced ejection fraction, compared with healthy subjects (HF with reduced ejection fraction: 834.4 95% CI, 628.4-1040.3 pg/mL, n=40; controls: 146.0 86.3-205.7 pg/mL, n=20,
=1.9×10
). There was clear FGF21 staining in diseased cardiomyocytes, and circulating FGF21 levels negatively correlated with the expression of cardiac genes involved in ketone metabolism, consistent with cardiac FGF21 signaling. FGF21 gene expression was very low in failing and nonfailing hearts, suggesting extracardiac production of the circulating hormone. Circulating FGF21 levels were correlated with BNP (B-type natriuretic peptide) and total bilirubin, markers of chronic cardiac and hepatic congestion.
Circulating FGF21 levels are elevated in HF with reduced ejection fraction and appear to bind to the heart. The liver is likely the main extracardiac source. This supports a model of hepatic FGF21 communication to diseased cardiomyocytes, defining a potential cardiohepatic signaling circuit in human HF.
Early-onset psychosis (EOP) refers to the development of psychosis before the age of 18 years. We aimed to summarize, for the first time, the meta-analytical evidence in the field of this vulnerable ...population and to provide evidence-based recommendations.
We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)–compliant, pre-registered (PROSPERO: CRD42022350868) systematic review of several databases and registers to identify meta-analyses of studies conducted in EOP individuals to conduct an umbrella review. Literature search, screening, data extraction, and quality assessment were carried out independently. Results were narratively reported, clustered across core domains. Quality assessment was performed with the Assessment of Multiple Systematic Reviews–2 (AMSTAR-2) tool.
A total of 30 meta-analyses were included (373 individual studies, 25,983 participants, mean age 15.1 years, 38.3% female). Individuals with EOP showed more cognitive impairments compared with controls and individuals with adult/late-onset psychosis. Abnormalities were observed meta-analytically in neuroimaging markers but not in oxidative stress and inflammatory response markers. In all, 60.1% of EOP individuals had a poor prognosis. Clozapine was the antipsychotic with the highest efficacy for overall, positive, and negative symptoms. Tolerance to medication varied among the evaluated antipsychotics. The risk of discontinuation of antipsychotics for any reason or side effects was low or equal compared to placebo.
EOP is associated with cognitive impairment, involuntary admissions, and poor prognosis. Antipsychotics can be efficacious in EOP, but tolerability and safety need to be taken into consideration. Clozapine should be considered in EOP individuals who are resistant to 2 non-clozapine antipsychotics. Further meta-analytical research is needed on response to psychological interventions and other prognostic factors.
This umbrella review summarized the meta-analytical knowledge from 30 meta-analyses on early-onset psychosis. Early-onset psychosis refers to the development of psychosis before the age of 18 years and is associated with cognitive impairment, hospitalization, and poor prognosis. Individuals with early-onset psychosis show more cognitive impairments and abnormalities compared with controls. Clozapine was the antipsychotic with the highest efficacy for positive, negative, and overall symptoms and should be considered in individuals with early-onset psychosis.
Early Onset Psychosis: Umbrella Review on Diagnosis, Prognosis and Treatment factors; https://www.crd.york.ac.uk/PROSPERO/; CRD42022350868.
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